3. Dimension reduction
Cankun Wang
09/21/2021
1 Set working dir
## [1] "Current working directory: C:/Users/flyku/Documents/GitHub/NOTCH1-scRNAseq/rmarkdown"2 Load data
3 Dimension reduction
Here we only want to visualize the sample differences in one UMAP. The batch removal is actually not needed as the cell types are defined by checking provided marker geners at each cell, the seurat clusters won’t be used for downstream analysis.
We adjusted UMAP neighbors and distance paramsters to make the visualization more ‘spread’
## Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck
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## Number of nodes: 25000
## Number of edges: 900161
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## Running Louvain algorithm...
## Maximum modularity in 10 random starts: 0.9691
## Number of communities: 15
## Elapsed time: 3 seconds4 2D
5 3D
6 Session info
## R version 4.1.0 (2021-05-18)
## Platform: x86_64-w64-mingw32/x64 (64-bit)
## Running under: Windows 10 x64 (build 19042)
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## Matrix products: default
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## locale:
## [1] LC_COLLATE=Chinese (Simplified)_China.936
## [2] LC_CTYPE=Chinese (Simplified)_China.936
## [3] LC_MONETARY=Chinese (Simplified)_China.936
## [4] LC_NUMERIC=C
## [5] LC_TIME=Chinese (Simplified)_China.936
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## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
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## other attached packages:
## [1] plotly_4.9.4.1 Polychrome_1.3.1 qs_0.25.1 here_1.0.1
## [5] patchwork_1.1.1 ggplot2_3.3.5 dplyr_1.0.6 cowplot_1.1.1
## [9] SeuratObject_4.0.2 Seurat_4.0.4
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## loaded via a namespace (and not attached):
## [1] Rtsne_0.15 colorspace_2.0-1 deldir_0.2-10
## [4] ellipsis_0.3.2 ggridges_0.5.3 rprojroot_2.0.2
## [7] spatstat.data_2.1-0 farver_2.1.0 leiden_0.3.9
## [10] listenv_0.8.0 ggrepel_0.9.1 RSpectra_0.16-0
## [13] fansi_0.5.0 codetools_0.2-18 splines_4.1.0
## [16] knitr_1.33 polyclip_1.10-0 jsonlite_1.7.2
## [19] ica_1.0-2 cluster_2.1.2 png_0.1-7
## [22] uwot_0.1.10 shiny_1.6.0 sctransform_0.3.2
## [25] spatstat.sparse_2.0-0 compiler_4.1.0 httr_1.4.2
## [28] assertthat_0.2.1 Matrix_1.3-4 fastmap_1.1.0
## [31] lazyeval_0.2.2 later_1.2.0 htmltools_0.5.1.1
## [34] tools_4.1.0 igraph_1.2.6 gtable_0.3.0
## [37] glue_1.4.2 RANN_2.6.1 reshape2_1.4.4
## [40] Rcpp_1.0.7 scattermore_0.7 jquerylib_0.1.4
## [43] vctrs_0.3.8 nlme_3.1-152 crosstalk_1.1.1
## [46] lmtest_0.9-38 xfun_0.25 stringr_1.4.0
## [49] globals_0.14.0 mime_0.10 miniUI_0.1.1.1
## [52] lifecycle_1.0.0 irlba_2.3.3 goftest_1.2-2
## [55] future_1.22.1 MASS_7.3-54 zoo_1.8-9
## [58] scales_1.1.1 spatstat.core_2.1-2 promises_1.2.0.1
## [61] spatstat.utils_2.2-0 parallel_4.1.0 RColorBrewer_1.1-2
## [64] yaml_2.2.1 reticulate_1.20 pbapply_1.4-3
## [67] gridExtra_2.3 sass_0.4.0 rpart_4.1-15
## [70] stringi_1.6.1 highr_0.9 rlang_0.4.11
## [73] pkgconfig_2.0.3 matrixStats_0.60.1 evaluate_0.14
## [76] lattice_0.20-44 ROCR_1.0-11 purrr_0.3.4
## [79] tensor_1.5 labeling_0.4.2 htmlwidgets_1.5.3
## [82] tidyselect_1.1.1 parallelly_1.27.0 RcppAnnoy_0.0.18
## [85] plyr_1.8.6 magrittr_2.0.1 R6_2.5.1
## [88] generics_0.1.0 DBI_1.1.1 pillar_1.6.2
## [91] withr_2.4.2 mgcv_1.8-36 fitdistrplus_1.1-5
## [94] scatterplot3d_0.3-41 survival_3.2-11 abind_1.4-5
## [97] tibble_3.1.2 future.apply_1.8.1 crayon_1.4.1
## [100] KernSmooth_2.23-20 utf8_1.2.1 RApiSerialize_0.1.0
## [103] spatstat.geom_2.2-0 rmarkdown_2.10 grid_4.1.0
## [106] data.table_1.14.0 digest_0.6.27 xtable_1.8-4
## [109] tidyr_1.1.3 httpuv_1.6.1 RcppParallel_5.1.4
## [112] stringfish_0.15.2 munsell_0.5.0 viridisLite_0.4.0
## [115] bslib_0.2.5.1